Precision Nanomedicine with Bio-Inspired Nanosystems: Recent Trends and Challenges in Mesenchymal Stem Cells Membrane-Coated Bioengineered Nanocarriers in Targeted Nanotherapeutics.

In the recent past, the formulation and development of nanocarriers has been elaborated into the broader fields and opened various avenues in their preclinical and clinical applications. In particular, the cellular membrane-based nanoformulations have been formulated to surpass and surmount the limitations and restrictions associated with naïve or free forms of therapeutic compounds and circumvent various physicochemical and immunological barriers including but not limited to systemic barriers, microenvironmental roadblocks, and other cellular or subcellular hinderances-which are quite heterogeneous throughout the diseases and patient cohorts. These limitations in drug delivery have been overcome through mesenchymal cells membrane-based precision therapeutics, where these interventions have led to the significant enhancements in therapeutic efficacies. However, the formulation and development of nanocarriers still focuses on optimization of drug delivery paradigms with a one-size-fits-all resolutions. As mesenchymal stem cell membrane-based nanocarriers have been engineered in highly diversified fashions, these are being optimized for delivering the drug payloads in more and better personalized modes, entering the arena of precision as well as personalized nanomedicine. In this Review, we have included some of the advanced nanocarriers which have been designed and been utilized in both the non-personalized as well as precision applicability which can be employed for the improvements in precision nanotherapeutics. In the present report, authors have focused on various other aspects of the advancements in stem cells membrane-based nanoparticle conceptions which can surmount several roadblocks and barriers in drug delivery and nanomedicine. It has been suggested that well-informed designing of these nanocarriers will lead to appreciable improvements in the therapeutic efficacy in therapeutic payload delivery applications. These approaches will also enable the tailored and customized designs of MSC-based nanocarriers for personalized therapeutic applications, and finally amending the patient outcomes.

Efficacy, immunogenicity, and safety of a monovalent mRNA vaccine, ABO1020, in adults: A randomized, double-blind, placebo-controlled, phase 3 trial.

BACKGROUND: ABO1020 is a monovalent COVID-19 mRNA vaccine. Results from a phase 1 trial showed ABO1020 was safe and well tolerated, and phase 3 trials to evaluate the efficacy, immunogenicity, and safety of ABO1020 in healthy adults are urgently needed. METHODS: We conducted a multinational, randomized, placebo-controlled, double-blind, phase 3 trial among healthy adults (ClinicalTrials.gov: NCT05636319). Participants were randomly assigned (1:1) to receive either 2 doses of ABO1020 (15 µg per dose) or placebo, administered 28 days apart. The primary endpoint was the vaccine efficacy in preventing symptomatic COVID-19 cases that occurred at least 14 days post-full vaccination. The second endpoint included the neutralizing antibody titers against Omicron BA.5 and XBB and safety assessments. FINDINGS: A total of 14,138 participants were randomly assigned to receive either vaccine or placebo (7,069 participants in each group). A total of 366 symptomatic COVID-19 cases were confirmed 14 days after the second dose among 93 participants in the ABO1020 group and 273 participants in the placebo group, yielding a vaccine efficacy of 66.18% (95% confidence interval: 57.21-73.27, p < 0.0001). A single dose or two doses of ABO1020 elicited potent neutralizing antibodies against both BA.5 and XBB.1.5. The safety profile of ABO1020 was characterized by transient, mild-to-moderate fever, pain at the injection site, and headache. CONCLUSION: ABO1020 was well tolerated and conferred 66.18% protection against symptomatic COVID-19 in adults. FUNDING: National Key Research and Development Project of China, Innovation Fund for Medical Sciences from the CAMS, National Natural Science Foundation of China.

Deep learning-based segmentation of left ventricular myocardium on dynamic contrast-enhanced MRI: a comprehensive evaluation across temporal frames.

PURPOSE: Cardiac perfusion MRI is vital for disease diagnosis, treatment planning, and risk stratification, with anomalies serving as markers of underlying ischemic pathologies. AI-assisted methods and tools enable accurate and efficient left ventricular (LV) myocardium segmentation on all DCE-MRI timeframes, offering a solution to the challenges posed by the multidimensional nature of the data. This study aims to develop and assess an automated method for LV myocardial segmentation on DCE-MRI data of a local hospital. METHODS: The study consists of retrospective DCE-MRI data from 55 subjects acquired at the local hospital using a 1.5 T MRI scanner. The dataset included subjects with and without cardiac abnormalities. The timepoint for the reference frame (post-contrast LV myocardium) was identified using standard deviation across the temporal sequences. Iterative image registration of other temporal images with respect to this reference image was performed using Maxwell's demons algorithm. The registered stack was fed to the model built using the U-Net framework for predicting the LV myocardium at all timeframes of DCE-MRI. RESULTS: The mean and standard deviation of the dice similarity coefficient (DSC) for myocardial segmentation using pre-trained network Net_cine is 0.78 ± 0.04, and for the fine-tuned network Net_dyn which predicts mask on all timeframes individually, it is 0.78 ± 0.03. The DSC for Net_dyn ranged from 0.71 to 0.93. The average DSC achieved for the reference frame is 0.82 ± 0.06. CONCLUSION: The study proposed a fast and fully automated AI-assisted method to segment LV myocardium on all timeframes of DCE-MRI data. The method is robust, and its performance is independent of the intra-temporal sequence registration and can easily accommodate timeframes with potential registration errors.

Recent Advancements in the Field of Chitosan/Cellulose-Based Nanocomposites for Maximizing Arsenic Removal from Aqueous Environment.

Water remediation, acknowledged as a significant scientific topic, guarantees the safety of drinking water, considering the diverse range of pollutants that can contaminate it. Among these pollutants, arsenic stands out as a particularly severe threat to human health, significantly compromising the overall quality of life. Despite widespread awareness of the harmful effects of arsenic poisoning, there remains a scarcity of literature on the utilization of biobased polymers as sustainable alternatives for comprehensive arsenic removal in practical concern. Cellulose and chitosan, two of the most prevalent biopolymers in nature, provide a wide range of potential benefits in cutting-edge industries, including water remediation. Nanocomposites derived from cellulose and chitosan offer numerous advantages over their larger equivalents, including high chelating properties, cost-effective production, strength, integrity during usage, and the potential to close the recycling loop. Within the sphere of arsenic remediation, this Review outlines the selection criteria for novel cellulose/chitosan-nanocomposites, such as scalability in synthesis, complete arsenic removal, and recyclability for technical significance. Especially, it aims to give an overview of the historical development of research in cellulose and chitosan, techniques for enhancing their performance, the current state of the art of the field, and the mechanisms underlying the adsorption of arsenic using cellulose/chitosan nanocomposites. Additionally, it extensively discusses the impact of shape and size on adsorbent efficiency, highlighting the crucial role of physical characteristics in optimizing performance for practical applications. Furthermore, this Review addresses regeneration, reuse, and future prospects for chitosan/cellulose-nanocomposites, which bear practical relevance. Therefore, this Review underscores the significant research gap and offers insights into refining the structural features of adsorbents to improve total inorganic arsenic removal, thereby facilitating the transition of green-material-based technology into operational use.

Adverse cardiovascular outcomes associated with proton pump inhibitor use after percutaneous coronary intervention: a systematic review and meta-analysis.

BACKGROUND: Proton pump inhibitors (PPIs) are commonly prescribed for gastroprotection in patients undergoing percutaneous coronary intervention (PCI), who are at increased risk of gastrointestinal bleeding due to antiplatelet therapy. However, emerging evidence suggests that PPIs may adversely impact cardiovascular outcomes. This systematic review and meta-analysis sought to assess the relationship between using PPIs and cardiovascular outcomes in patients following PCI. METHODS: We searched various databases up to March 15, 2024, for observational studies and randomized controlled trials (RCTs) assessing the cardiovascular effects of PPIs in PCI patients. Data were extracted on study characteristics, patient demographics, PPI use, and cardiovascular outcomes. The Newcastle-Ottawa Scale and Cochrane Risk of Bias Tool 2 assessed study quality. Meta-analyses were conducted using a random-effects model using R software version 4.3. RESULTS: A total of 21 studies involving diverse populations and study designs were included. Observational studies suggested a moderate increase in risk for composite cardiovascular diseases (CVD), myocardial infarction (MI), and major adverse cardiac events (MACE) associated with PPI use, with pooled hazard ratios (HRs) of 1.20 (95% CI: 1.093-1.308) for CVD, 1.186 (95% CI: 1.069-1.303) for MI, and 1.155 (95% CI: 1.001-1.309) for MACE. However, RCTs showed no significant link between PPI therapy and negative cardiovascular events (Relative Risk: 1.016, 95% CI: 0.878-1.175). Substantial heterogeneity was observed among observational studies but not RCTs. CONCLUSION: The findings indicate that while observational studies suggest a potential risk of adverse cardiovascular events with post-PCI use of PPI, RCTs do not support this association. Further large-scale, high-quality studies are required to understand the cardiovascular implications of individual PPIs better and optimize patient management post-PCI. This analysis shows the complexity of PPI use in patients with coronary artery diseases and the necessity to balance gastroprotective benefits against potential cardiovascular risks.

Insights into Allosteric Inhibition of the AcrB Efflux Pump: Role of Distinct Binding Pockets, Protomer Preferences, and Crosstalk Disruption.

AcrB, a key component in bacterial efflux processes, exhibits distinct binding pockets that influence inhibitor interactions. In addition to the well-known distal binding pocket within the periplasmic domain, a noteworthy pocket amidst the transmembrane (TM) helices serves as an alternate binding site for inhibitors. The bacterial efflux mechanism involves a pivotal functional rotation of the TM protein, inducing conformational changes in each protomer and propelling drugs toward the outer membrane domain. Surprisingly, inhibitors binding to the TM domain display a preference for L protomers over T protomers. Metadynamics simulations elucidate that Lys940 in the TM domain of AcrB can adopt two conformations in L protomers, whereas the energy barrier for such transitions is higher in T protomers. This phenomenon results in stable inhibitor binding in l protomers. Upon a detailed analysis of unbinding pathways using random accelerated molecular dynamics and umbrella sampling, we have identified three distinct routes for ligand exit from the allosteric site, specifically involving regions within the TM domains─TM4, TM5, and TM10. To explore allosteric crosstalk, we focused on the following key residues: Val452 from the TM domain and Ala831 from the porter domain. Surprisingly, our findings reveal that inhibitor binding disrupts this communication. The shortest path connecting Val452 and Ala831 increases upon inhibitor binding, suggesting sabotage of the natural interdomain communication dynamics. This result highlights the intricate interplay between inhibitor binding and allosteric signaling within our studied system.

Genome-wide comparative analyses highlights selection signatures underlying saline adaptation in Chilika buffalo.

Chilika, a native buffalo breed of the Eastern coast of India, is mainly distributed around the Chilika brackish water lake connected with the Bay of Bengal Sea. This breed possesses a unique ability to delve deep into the salty water of the lake and stay there to feed on local vegetation of saline nature. Adaptation to salinity is a genetic phenomenon, however, the genetic basis underlying the salinity tolerance is still limited in animals specifically in livestock. The present study explores the genetic evolution that unveils the Chilika buffalo's adaptation to the harsh saline habitat (water and food system). For this study, whole genome resequencing data on 18 Chilika buffalo and for comparison 10 Murrah buffalo of normal habitat were generated. For identification of selection sweeps, intrapopulation and interpopulation statistics were employed. A total of 709, 309, 468, and 354 genes were detected having selection sweeps in Chilika buffalo using the nucleotide diversity (θπ), Tajima's D, nucleotide diversity ratio (θπ-ratio), and FST methods, respectively. Further analysis revealed a total of 23 genes including EXOC6B, VPS8, LYPD1, VPS35, CAMKMT, NCKAP5, COMMD1, MYLK3, B3GNT2 were found to be common by all the methods. Furthermore, functional annotation study of identified genes provided pathways such as MAPK signaling, renin secretion, endocytosis, oxytocin signaling pathway, etc. Gene network analysis enlists hub genes, provide insights into their interactions with each other. In conclusion, this study has highlighted the genetic basis underlying the local adaptive function of Chilika buffalo under saline environment.

Treatment intensification in Kawasaki disease - current perspectives.

INTRODUCTION: Intravenous immunoglobulin is the standard of care in Kawasaki disease. However, a subset of patients exhibits resistance to intravenous immunoglobulin treatment, even when Kawasaki disease is promptly diagnosed and managed. While intravenous immunoglobulin reduces the occurrence of coronary artery abnormalities from 15-25% to 3-5%, it does not entirely eliminate the risk. Besides, management guidelines for non-coronary complications of Kawasaki disease, for instance, myocarditis, remain speculative. AREAS COVERED: Recent literature suggests that a subset of patients with Kawasaki disease may benefit from treatment intensification with drugs, such as corticosteroids, infliximab, anakinra, and/or ciclosporin. In this manuscript, we have reviewed recent advances in the management of Kawasaki disease, especially with regard to preemptive intensification of therapy in children at high risk of cardiac complications. A comprehensive search was made using Web of Science, Scopus, and PubMed databases to gather English articles published from 1967 to 2023 on the treatment of Kawasaki disease. We incorporated the following words in the search strategy: 'Kawasaki disease,' 'intravenous immunoglobulin/IVIg,' 'intravenous immunoglobulin/IVIg-resistant Kawasaki disease,' 'treatment intensification,' or 'primary intensification of treatment/therapy.' EXPERT OPINION: The 'high-risk' group in Kawasaki disease needs to be identified with early intensification of primary therapy for better coronary and myocardial outcomes.

The severity of non-smoking chronic obstructive pulmonary disease is correlated with biomass fuel exposure and COPD assessment test score.

BACKGROUND AND OBJECTIVE: Tobacco smoking is an established risk factor for chronic obstructive pulmonary disease (COPD). Current evidence suggests that non-tobacco-related risk factors vary geographically and are less understood than smoking. This study aims to compare the risk factors, symptoms, and clinical features of smoking (S-COPD) and non-smoking (NS-COPD) in a COPD population. MATERIALS AND METHODS: In this retrospective cross-sectional study, 489 COPD patients were screened. Data on socio-demographics, smoking and medical history, other risk factors, symptoms, and clinical characteristics including COPD Assessment Test (CAT) score, and Modified Medical Research Council (mMRC) Dyspnea Scale were examined. RESULTS: Of the total selected 416 COPD patients, 35.34% were NS-COPD while 64.66% were S-COPD. S-COPD was predominant in males, whereas NS-COPD was predominant in females (P < 0.0001). In NS-COPD, biomass fuel exposure was a major risk factor (P < 0.0001), and 61% of subjects had a biomass fuel exposure index of >60. In bivariate and multivariate analyses, no risk factors were correlated with forced expiratory volume in 1 second (FEV1)% predicted, while among clinical features, duration of illness (P = 0.001) was correlated with lower values of FEV1 in the multivariate table of S-COPD. In the multivariate analysis, biomass fuel exposure (P = 0.039) and CAT score (P < 0.0001) were correlated with FEV1(%) in NS-COPD. CONCLUSION: Biomass fuel exposure is a substantial risk factor for NS-COPD and was correlated with FEV1(%) predicted. In addition, the CAT score correlated with disease severity in patients with NS-COPD. The development of COPD in non-smokers is being recognized as a separate phenotype and it should be managed according to risk factors.

Public Health System's Preparedness to Address Polycystic Ovarian Syndrome: A Rapid Assessment Survey of Health-care Providers in India.

BACKGROUND: Polycystic ovarian syndrome (PCOS) is one of the most common endocrine disorders largely affecting women of reproductive age group. OBJECTIVES: This study aimed to understand the Indian public health-care systems' preparedness in addressing PCOS. MATERIALS AND METHODS: A multicentric rapid assessment cross-sectional study was undertaken among 173 health-care providers serving across various public health-care facilities in India. This study was a component of a larger task force study that aimed to estimate the community-based prevalence of PCOS in India. Information on PCOS cases reported that knowledge about PCOS diagnosis, management practices, availability of diagnostic facilities, and drugs was explored. RESULTS: Irregular menstrual cycle was the most commonly reported PCOS symptom. Most of the health-care providers (HCPs) lacked correct knowledge about diagnostic criteria and investigation needed for the diagnosis of PCOS. Diagnostic facilities and drugs were inadequate. However, some facilities had access to investigations through public-private partnerships. Awareness programs on PCOS in the community were negligible, and PCOS cases were not documented. Training HCPs on PCOS along with the availability of specialists and strengthening diagnostic facilities were some major demands from the HCPs. CONCLUSION: Results suggest the need for training HCPs, strengthening infrastructure with good referral linkages, and adequate supply of drugs to help improve PCOS management at public health-care facilities in India. There is a need to develop national technical and operational guidelines to address PCOS using a multidisciplinary approach across all levels of care. Creating demand for services and advocating healthy lifestyles through community awareness can help early diagnosis and prevention of complications.

Evaluating Carcinoembryonic Antigen and Glucose Levels in Pancreatic Cyst Fluid for Mucinous Versus Non-mucinous Differentiation.

BACKGROUND: A more precise identification of mucinous cysts will lower the likelihood of needless pancreatic surgery. Pancreatic cyst fluid (PCF) contains glucose and carcinoembryonic antigen (CEA), which serve as biomarkers to differentiate mucinous from non-mucinous pancreatic cystic neoplasms (PCNs). OBJECTIVE: To evaluate the diagnostic accuracy of combined CEA and glucose levels in PCF for distinguishing mucinous from non-mucinous PCNs preoperatively. METHODS: After receiving approval from the Institutional Ethical Committee of Indira Gandhi Institute of Medical Sciences, Patna, a cross-sectional validation research was carried out. All patients ≥18 years of age who had undergone pancreatic surgery or endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) for a pancreatic cystic lesion and for whom PCF was acquired were eligible for inclusion. Patients were excluded if there was no PCF available, if they had been diagnosed with an extrapancreatic illness (such as ampullary adenoma), or if they could not be excluded due to pancreatic cancer generated from PCN. Diagnoses were pathologically confirmed. We performed measurements for CEA and glucose in PCF. CEA and glucose were measured using an Architect i2000SR analyzer (Abbott, Lake County, IL) and AU 5800 Beckman Coulter (Brea, CA), respectively. Diagnostic accuracy was evaluated by receiver operator characteristic (ROC) curves. RESULTS: PCF was obtained from 100 patients, of whom 54 (54%) had mucinous PCN and 46 (46%) had non-mucinous PCN. When CEA (cut-off ≥ 151 ng/ml) and glucose levels (cut-off ≤ 50 mg/dL) were combined, the results showed 46% sensitivity and 92% specificity. However, when CEA (cut-off ≥ 17 ng/ml) or glucose testing (cut-off ≤ 50 mg/dL) was used separately, the results showed 82% sensitivity and 73% specificity. CONCLUSION: The combined CEA and glucose testing in PCF demonstrated high specificity and sensitivity for differentiating mucinous from non-mucinous PCNs, suggesting its potential utility in preoperative diagnosis.

Predictive Value of C-reactive Protein in the Spontaneous Passage of Lower Ureteric Stones: A Prospective Single-Centre Study.

INTRODUCTION: Ureteric stones, characterised by their presence in the ureter, present a common yet often painful urological condition requiring timely intervention. As C-reactive protein (CRP) emerges as a potential biomarker, its correlation with the spontaneous stone passage (SSP) offers valuable insights into patient management and treatment strategies. The present study aimed to assess if CRP levels can predict SSP in symptomatic lower ureteric calculi of size 5 mm-10 mm. MATERIALS AND METHODS: This prospective observational study, conducted at the Indira Gandhi Institute of Medical Sciences in Patna, India, from July 2022 to June 2023, focused on individuals aged 13 to 60 years presenting with ureteric colic and single distal ureteral stones (5 mm-10 mm). Patients underwent comprehensive initial assessment and monitoring, including diagnostic procedures such as a complete blood count, urinalysis, CRP levels, and renal function evaluations. Treatment consisted of hydration encouragement, tamsulosin (0.4 mg) daily administration, and diclofenac (50 mg) as needed. Follow-up assessments at one-month post-treatment involved clinical examination and imaging studies to evaluate treatment efficacy. RESULTS: This study analysed 157 patients with ureteric stones, finding that 76% experienced SSP. Lower CRP levels (≤6 mg/L), along with other laboratory parameters like low white blood cell counts, low neutrophil levels, absence of leukocyturia, absence of hematuria, and lower urine specific gravity, were associated with higher SSP rates. C-reactive protein levels ≤6 mg/L emerged as a strong predictor of SSP in multiple regression analysis. CONCLUSION: The findings underscore the potential utility of CRP as a predictive biomarker in guiding the management and treatment strategies for ureteric stones.

Impact of age at first calving on fertility and production performance in Murrah buffalo.

The present study analyses the effect of age at first calving (AFC) on future fertility and productivity in Murrah buffaloes. The data of 314 buffalo heifers of animal farm section, ICAR-CIRB, Hisar were collected over a period of 9 years from 2010 to 2018. The buffalo heifers were categorized into six groups according to the AFC named as 30-35, 36-41, 42-47, 48-53, 54-59 and 60-65 months. The influence of AFC on standard lactation milk (SLMY), peak yield (PY), days in milk (DIM), calving to first service, service per conception, calving to conception interval (CCI) and calving interval till fifth lactation were studied. The study revealed poor productive traits in buffalo heifers calved at younger age (30-35 months) during first parity. The productive value positively corresponded with increase in AFC. During successive lactations, higher mean milk yield (SLMY and PY) was found in groups with 36-41, 42-47 and 48-53 months. The mean number of services per conception was lower in buffalo heifers with 36-41 and 42-47 months following first calving till fifth lactation. Similarly, the said groups had lower mean calving to first service, CCI and CI up to fifth lactation. The survival rate was higher in heifers with AFC 36-41, 42-47, 48-53 and 54-59 months than with AFC 30-35 and 60-65 months. The buffalo heifers with 36-41 and 42-47 months of AFC had higher survival rate and better productive and reproductive traits till fifth parity in the current study. The study concluded that a minimum ideal AFC of 36-41 months yielded the highest productive gain.

Natural hypoglycaemic bioactives: Newer avenues and newer possibilities.

The incidences of endocrine and metabolic disorders like diabetes have increased worldwide. Several proposed molecular pathways mechanisms for the management of diabetes have been identified, but glycaemic control is still a challenging task in the drug discovery process. Most of the drug discovery processes lead to numerous scaffolds that are prominent in natural products. The review deals with the natural bioactives as an α-amylase inhibitors, α-glucosidase inhibitors, protein tyrosine phosphatase-1B inhibitors, dipeptidyl peptidase-IV inhibitors, G-protein coupled receptors-40 agonists, PPAR-γ agonists and the activators of 5'-adenosine monophosphate-activated protein kinase and glucokinase. So, in this review, we focused on the hypoglycaemic bioactives, which will assist scientific developers, traditional medicinal practitioners, and readers to discover some potent antidiabetic molecules. Strategies like chemometric approaches, scaffold hopping, and total synthesis of natural products by group modification or ring opening/closing mechanism could be useful for the development of novel hit/lead antidiabetic molecules. The study concludes that each phyto molecule inherits a potential to get explored by repurposing techniques for various antidiabetic targets and offer an alternative antidiabetic therapeutic medicinal potential.

Lipidic Nanosystem as State-of-the-Art Nanovehicle for Biomedical Applications.

Lipids have tremendously transformed the biomedical field, especially in the last few decades. Nanosystems, especially Lipid nanocapsules (LNCs), have emerged as the most demanding nanovehicle systems for delivering drugs, genes, and other diagnostic agents. Unique attributes and characteristic features such as higher encapsulation efficiency, stealth effect, ability to solubilize a wide range of drugs, capability to inhibit P-gp efflux pumps, and higher stability play a vital role in engaging this nanosystem. LNCs are a lipid-based nano-drug delivery method that combines the most significant traits of liposomes with polymeric nanoparticles. Structurally, LNCs have an oily core consisting of medium and long triglycerides and an aqueous phase encased in an amphiphilic shell. This manuscript crosstalks LNCs for various biomedical applications. A detailed elaboration of the structural composition, methods of preparation, and quality control aspects has also been attained, with particular emphasis on application approaches, ongoing challenges, and their possible resolution. The manuscript also expounds the preclinical data and discusses the patents atlas of LNCs to assist biomedical scientists working in this area and foster additional research. Supplementary Information: The online version contains supplementary material available at 10.1007/s12088-024-01298-3.

MK2 inhibitor PF-3644022 shows protective effect in mouse microglial N9 cell line induced with cigarette smoke extract.

Neuroinflammation is suggested as one of the potential links between CS-induced neuronal dysfunction. Cigarette smoke (CS) is one of the significant contributors of neuroinflammation, consequently leading to cognitive impairment and neurodegeneration. Microglia are the key resident macrophage cells in the brain with cell surface TLR4 receptor for responding to various stress signals. The CS constituents promote inflammation and oxidative stress in microglia leading to cytotoxicity through the TLR4-MK2 axis. However, the role of MK2 kinase in CS-induced microglial inflammation is not yet clearly understood. Therefore, we have used an MK2 inhibitor, PF-3644022 to study modulation of CS-extract induced oxidative and inflammatory signaling in a mouse microglial cell line, Furthermore, we also evaluated the enzymatic activity of acetylcholinesterase (AChE) on a direct exposure of enzyme with CS. CS exposure led to microglial cytotoxicity and enhanced the level of oxidative stress and proinflammatory cytokine release by microglial cells. The microglial cells pretreated with MK2 inhibitor, PF-3644022 significantly reduced the levels of oxidative stress markers, proinflammatory markers, and improved the level of antioxidant proteins in these cells. In addition, direct exposure of CS showed reduction in the enzymatic activity of AChE.

Navigating the future of health care with AI-driven digital therapeutics.

Digital therapeutics (DTx) is a recently conceived idea in health care that aims to cure ailments and modify patient behavior by employing a range of digital technologies. Notably, when traditional medication is not entirely efficacious, DTx offers an innovative avenue for treatments linked to dysfunctional behaviors and lifestyle management. DTx involves extremely adaptable therapeutic devices that empower greater patient engagement in treating illness, using algorithms to collect, transfer and analyze the patient's data. Efficient clinical monitoring and supervision at the individual level by remote access and algorithms for a range of diseases is made possible by integrating machine learning and artificial intelligence with DTx. There is a potentially large worldwide market for DTx owing to its convenient, personalized therapies.

Automatic removal of large blood vasculature for objective assessment of brain tumors using quantitative dynamic contrast-enhanced magnetic resonance imaging.

The presence of a normal large blood vessel (LBV) in a tumor region can impact the evaluation of quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters and tumor classification. Hence, there is a need for automatic removal of LBVs from brain tissues including intratumoral regions for achieving an objective assessment of tumors. This retrospective study included 103 histopathologically confirmed brain tumor patients who underwent MRI, including DCE-MRI data acquisition. Quantitative DCE-MRI analysis was performed for computing various parameters such as wash-out slope (Slope-2), relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF), blood plasma volume fraction (Vp), and volume transfer constant (Ktrans). An approach based on data-clustering algorithm, morphological operations, and quantitative DCE-MRI maps was proposed for the segmentation of normal LBVs in brain tissues, including the tumor region. Here, three widely used data-clustering algorithms were evaluated on two types of quantitative maps: (a) Slope-2, and (b) a new proposed combination of rCBV and Slope-2 maps. Fluid-attenuated inversion recovery-MRI hyperintense lesions were also automatically segmented using deep learning-based architecture. The accuracy of LBV segmentation was qualitatively assessed blindly by two experienced observers, and Likert scoring was also obtained from each individual and compared using Cohen's Kappa test, and multiple statistical features from quantitative DCE-MRI parameters were obtained in the segmented tumor. t-test and receiver operating characteristic (ROC) curve analysis were performed for comparing the effect of removal of LBVs on parameters as well as on tumor grading. k-means clustering exhibited better accuracy and computational efficiency. Tumors, in particular high-grade gliomas (HGGs), showed a high contrast compared with normal tissues (relative % difference = 18.5%) on quantitative maps after the removal of LBVs. Statistical features (95th percentile values) of all parameters in the tumor region showed a statistically significant difference (p < 0.05) between with and without LBV maps. Similar results were obtained for the ROC curve analysis for differentiation between low-grade gliomas and HGGs. Moreover, after the removal of LBVs, the rCBV, rCBF, and Vp maps show better visualization of tumor regions.

A study on production of hydrogen using Al scrap feedstock.

A sustainable future, concerning the energy transformation of a country, heavily relies on the availability of energy resources, particularly renewables such as solar, wind, hydropower, and clean hydrogen. Among these, hydrogen is the most promising energy source due to its high calorific value, ranging between 120 and 140 MJ/kg. It has the potential to lead the market in various industries such as power generation, steel, chemical, petrochemical, and automotive. Significant research has been going on in hydrogen production technologies to reduce costs and improve competitiveness with fossil fuels. One such potential approach includes the use of metal-water reactions, which offer unique opportunities for producing clean hydrogen and other valuable byproducts. However, the quantity of hydrogen produced varies depending on the metal feedstock, type of electrolyte, and the activator or catalyst, used in combination with water. This latest work discusses recent progress on hydrogen production and the effects of variations in different parameters on the process, with a focus on aluminum (Al)-water reactions. Investigations have been conducted and reported on the effect of various activators with different concentrations, the quantity of aluminum scrap feedstock, and the volume of the electrolyte on the kinetics of the metal-water reactions and hydrogen production. Sodium hydroxide (NaOH) was observed to be more effective than potassium hydroxide (KOH) in promoting metal-water reactions. These activator-assisted metal-water reactions help produce clean hydrogen, along with other value-added products such as hydroxides. This work clearly sheds light on the potential utilization of industrial aluminum scrap as feedstock for producing clean hydrogen.

An Update on Current Trend in Sample Preparation Automation in Bioanalysis: strategies, Challenges and Future Direction.

Automation in sample preparation improves accuracy, productivity, and precision in bioanalysis. Moreover, it reduces resource consumption for repetitive procedures. Automated sample analysis allows uninterrupted handling of large volumes of biological samples originating from preclinical and clinical studies. Automation significantly helps in management of complex testing methods where generation of large volumes of data is required for process monitoring. Compared to traditional sample preparation processes, automated procedures reduce associated expenses and manual error, facilitate laboratory transfers, enhance data quality, and better protect the health of analysts. Automated sample preparation techniques based on robotics potentially increase the throughput of bioanalytical laboratories. Robotic liquid handler, an automated sample preparation system built on a robotic technique ensures optimal laboratory output while saving expensive solvents, manpower, and time. Nowadays, most of the traditional extraction processes are being automated using several formats of online techniques. This review covered most of the automated sample preparation techniques reported till date, which accelerated and simplified the sample preparation procedure for bioanalytical sample analysis. This article critically analyzed different developmental aspects of automated sample preparation techniques based on robotics as well as conventional sample preparation methods that are accelerated using automated technologies.